“LinkedIn Time Traveling” and the Loneliness Problem AI Is Making Worse

Nick: Welcome to the Wellable Weekly Podcast, where we talk about key topics and trends at the intersection of wellbeing, technology, and HR. Geoff, your background looks a bit familiar. 

Geoff: A little role reversal here. I’m holding it down in our Boston fort. You’re over in Bangalore, right? 

Nick: I’m in Bangalore, yeah, recording with our India team out here. First time doing the podcast from Bangalore. Let’s dive right in. One of the things I love most about HR news is when you coin a new term for a modern phenomenon — like token maxing when AI became a thing, or quiet quitting during COVID. The first article is about a new term: LinkedIn time traveling. 

When I first heard it, I had no idea what to expect. Effectively, it’s employees going back to old jobs they had and updating the posting — sometimes updating the description, in extreme scenarios updating the title, but essentially refreshing their profile by going back pretty far into their work history. It’s probably an indication they’re hitting the job market. 

Geoff: Profile refreshing isn’t quite as catchy as time traveling, but that’s really what it is in practice. The article reported that one in five, almost 20% of LinkedIn users, have changed the title or description of a previous job after leaving the position. On the surface, if you look at LinkedIn as an extension of your resume, that’s not totally unusual. But what this article is calling attention to is that it’s going beyond freshening up. In some cases, job descriptions are being updated to the point of possible fabrication — inserting key terms around AI or other recent skill sets for jobs that likely did not cover those technologies, or referencing technologies that may not have even existed at the time. 

Nick: My favorite example in the article: an employee who worked at Amazon in 2017 updated their previous job description from “machine learning” to “machine learning and AI.” AI really wasn’t a mainstream thing in 2017. So you can see the extent to which people are trying to optimize and stretch their profiles. And it’s not just adding things. People are also removing references to DEI. If you had a bullet point about chairing a DEI committee, people are removing that given the current political environment. You can tell they’re doing all of this to market themselves as candidates. What’s also really interesting is that this analysis wasn’t some fringe publication — it was done by the National Bureau of Economic Research. They examined tens of millions of profiles. The sheer number of people going back to update their history is material. 

Geoff: It tells you a couple things. One, it continues to be a difficult job market. We’ve talked about the challenges applicants face — bot-screened interviews, massive application volumes, getting through the noise just to land a first-round interview. On the one hand, you have to respect the hustle and the desire to position yourself in the best light. But removing DEI references or inserting skills you didn’t have does feel like a growing audacity to put things out there regardless of whether they’re verifiable. There’s a broader cultural shift here — more willingness to state your claim boldly and not worry too much about whether every detail tracks. 

Nick: The article didn’t cover this, but I suspect a lot of the updated descriptions are AI-generated as well. You get a lot of extra fluffy language stuffed in. And I think people are recognizing that employers are using AI tools to screen applicants, and I’d assume some of those tools look at your public LinkedIn profile. So people are probably stuffing keywords specifically designed to get past AI screeners. Which connects to what Geoff was mentioning about the dead internet theory — this idea that at some not-so-distant point, most of what’s on the internet will be populated by bots and AI rather than people. It sounds far-fetched, but the way things are trending, it’s not out of the realm of possibility. 

Geoff: That concept connects directly to our next topic: the pervasive challenge of loneliness in the workplace. You’re increasingly interacting with AI technologies and bots rather than human coworkers, and that’s particularly acute in remote and hybrid environments. Full in-office settings have the lowest levels of loneliness. Hybrid is better than fully remote, but not by a lot. 

Nick: This is a classic example of AI taking a problem that already exists and making it much worse. The World Health Organization declared loneliness a global pandemic — I think it was right after COVID. And then they published that the mortality effects of loneliness are equivalent to smoking 15 cigarettes a day. That’s not a casual smoker. That’s a heavy smoker. Three-fourths of workers are using AI to seek advice rather than asking a colleague. Fifty-two percent use it for brainstorming rather than whiteboarding with a coworker. Some people are even using AI for companionship. The office is a place where companionship happens — some people’s best relationships are built in office settings. And 40% of people are using AI specifically for that interpersonal use case. 

And if you think about the incentives: 44% of employees choose AI over collaborating with a colleague because they believe it helps them get work done quicker. The one that really blew my mind is that the AI tool won’t challenge them. That’s why people prefer it. I get it when I think about it — top performers want to be challenged, but your average employee does not. And 37% use AI for brainstorming because of fear of judgment. If your company doesn’t openly appreciate all ideas, good and bad, people just run to AI. The incentives to use AI are real, the barriers to use it are low — and in that sense, it’s actually worse than the cigarette problem. With smoking, you have to leave the building and go outside. Everyone knows smoking isn’t making you more productive. AI has no comparable friction, and every use of it feels like a productivity decision. 

Imagine if you went to an employer and said more than 20% of your population is smoking 15 cigarettes a day. That company would have a tobacco cessation program, a surcharge, formal policies. When a similar stat comes out around loneliness, because it’s viewed as a personal problem, you don’t see employers responding the same way. If anything, they’re encouraging AI use in ways that may be exacerbating the problem. 

Geoff: Let’s think about some practical strategies. The most common day-to-day activity is treating AI as a search engine on steroids — getting advice, brainstorming tips, bouncing ideas. The guidance shouldn’t be to stop doing that. But the guidance should be to do some of that in a coworking setting. When you and I are brainstorming, we’ll pull up Gemini and ask it questions together. You go through that exercise of getting feedback from an AI tool, talking about it together, disseminating what’s real from what isn’t — and you do it as a group. That produces a better outcome and avoids the isolation. 

Nick: The same version of what you’re suggesting. We had a unique idea for a creative marketing strategy, and two of the marketing associates and I sat down together — remotely, on Teams — to work on it collectively. Everyone took ownership of different tasks, all heavily using AI. We needed a logo, a graphic, different deliverables. Someone generated something in AI, shared it with the team, got feedback, iterated. It was very fast, very successful, and the entire time I felt like I was working with the team. We could not have done it without AI, but AI didn’t replace the team — it accelerated what we built together. 

I heard something on a podcast recently that stuck with me. Someone said they don’t view AI as a tool — because a tool is like Excel or Word. AI is close to being another human. You wouldn’t call a human a tool. If you view AI as a person on your team, the natural response is to collaborate with them alongside your colleagues. That has to be the solution. Stack projects with multiple people even if you used to do them solo. Use AI as a team member in a shared setting, not a private oracle. If you do that, you still get the benefits of higher quality work and accelerated production without sacrificing social interaction. 

Geoff: It’s a lot about being deliberate and intentional. You can pick up efficiency gains, remove more menial tasks, and still benefit from the collaboration you normally would have with coworkers. The shared successes of a job well done together — that matters. And hopefully in less time, with a better quality product. On that note, thanks for those who tune in to Wellable Weekly. You can catch us on Apple Podcasts, Spotify, or wherever you get your podcasts. Be sure to subscribe to the Wellable Weekly newsletter for all of our insights there as well. Thank you.